Zeeshan Ahmed

Rutgers Health

In this article, we present IntelliGenes, a novel machine learning (ML) pipeline for the multi-genomics exploration to discover biomarkers significant in disease prediction with high accuracy. IntelliGenes is based on a novel approach, which consists of nexus of conventional statistical techniques and cutting-edge ML algorithms using multi-genomic,...

Periodontal diseases are chronic, inflammatory disorders that involve the destruction of supporting tissues surrounding the teeth which leads to permanent damage and substantially heightens systemic exposure. If left untreated, dental, oral, and craniofacial diseases (DOCs), especially periodontitis, can increase an individual’s risk in developing...

Personalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatm...

Artificial intelligence (AI) and machine learning (ML) have advanced in several areas and fields of life, however, its progress in the field of multi-omics is not matching the levels others have attained. Challenges include but are not limited to the handling and analysis of high volumes of complex multi-omics data, and the expertise needed to impl...

Recent technological advancements have vastly improved access to high-throughput biological instrumentation, sparking an unparalleled surge in omics data generation. The implementation of artificial intelligence techniques is revolutionizing omics data interpretation. The BMC Methods Collection "Artificial intelligence for omics data analysis" will...

Genome‐wide association studies (GWAS) have been instrumental in elucidating the genetic architecture of various traits and diseases. Despite the success of GWAS, inherent limitations such as identifying rare and ultra‐rare variants, the potential for spurious associations and pinpointing causative agents can undermine diagnostic capabilities. This...

Keywords: cardiovascular disease • GWAS • polygenic risk score • precision medicine • single nucleotide variants Big data, GWAS, polygenic risk scores & AI/ML Big data is a term used to describe extensive and wide data sets that are very intricate, convoluted, multifaceted and cannot be manually analyzed due to human error. Before big data, informa...

Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortali...

Personalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatm...

Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to...

Background Cardiovascular disease (CVD) is a leading cause of premature mortality in the United States and the world. CVD comprises several complex and mostly heritable conditions, which range from myocardial infarction to congenital heart disease. The risk factors contributing to the development of CVD and response to therapy in an individual pati...

A timely understanding of the biological secrets of complex diseases will ultimately benefit millions of individuals by reducing the high risks for mortality and improving the quality of life with personalized diagnoses and treatments. Due to the advancements in sequencing technologies and reduced cost, genomics data are developing at an unmatched...

Due to the advancements in sequencing technologies, genomics data is developing at an unmatched pace and levels to foster translational research. Over ten million genomics datasets have been produced and publicly shared in the year 2022. Genome-wide association studies (GWAS) have remarkably assisted in understanding the genetic basis of human dise...

Artificial intelligence for personalized and predictive genomics data analysis

Cardiovascular disease (CVD) is the leading cause of mortality and loss of disability adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) are associated with physical effects on the heart muscles. As a result of the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personali...

Cardiovascular disease (CVD) is a leading cause of premature mortality in the US and the world. CVD comprises of several complex and mostly heritable conditions, which range from myocardial infarction to congenital heart disease. Here, we report our findings from an integrative analysis of gene expression, disease-causing gene variants, and associa...

Timely understanding of biological secrets of complex diseases will ultimately benefit millions of individuals by reducing the high risks for mortality and improving the quality of life with personalized diagnoses and treatments. Due to the advancements in sequencing technologies and reduced cost, genomics data is developing at an unmatched pace an...

Precision medicine is driven by the paradigm shift of empowering clinicians to predict the most appropriate course of action for patients with complex diseases and to improve routine medical and public health practice. Understanding patients' multi-omics make-up in conjunction with the clinical data will lead to determining predisposition, diagnost...

Precision medicine uses genetic, environmental and lifestyle factors to more accurately diagnose and treat disease in specific groups of patients, and it is considered one of the most promising medical efforts of our time. The use of genetics is arguably the most data-rich and complex components of precision medicine. The grand challenge today is t...

Precision medicine has greatly aided in improving health outcomes using earlier diagnosis and better prognosis for chronic diseases. It makes use of clinical data associated with the patient as well as their multi-omics/genomic data to reach a conclusion regarding how a physician should proceed with a specific treatment. Compared to the symptom-dri...

Aim: A human immunogenetics variation study was conducted in samples collected from diverse COVID-19 populations. Materials & methods: Whole-genome and whole-exome sequencing (WGS/WES), data processing, analysis and visualization pipeline were applied to identify variants associated with genes of interest. Results: A total of 2886 mutations were fo...

Precision medicine is driven by the paradigm shift of empowering clinicians to predict the most appropriate course of action for patients with complex diseases and improve routine medical and public health practice. It promotes integrating collective and individualized clinical data with patient specific multi-omics data to develop therapeutic stra...

Background Heart failure (HF) is one of the most common complications of cardiovascular diseases (CVDs) and among the leading causes of death in the US. Many other CVDs can lead to increased mortality as well. Investigating the genetic epidemiology and susceptibility to CVDs is a central focus of cardiology and biomedical life sciences. Several stu...

Additional file 1 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

Additional file 2 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

Advancing frontiers of clinical research, we discuss the need for intelligent health systems to support a deeper investigation of COVID-19. We hypothesize that the convergence of the healthcare data and staggering developments in artificial intelligence have the potential to elevate the recovery process with diagnostic and predictive analysis to id...

Supplementary Material: JWES: A new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping

Whole genome and exome sequencing (WGS/WES) are the most popular next-generation sequencing (NGS) methodologies and are at present often used to detect rare and common genetic variants of clinical significance. We emphasize that automated sequence data processing, management, and visualization should be an indispensable component of modern WGS and...

Over the last few decades, genomics is leading toward audacious future, and has been changing our views about conducting biomedical research, studying diseases, and understanding diversity in our society across the human species. The whole genome and exome sequencing (WGS/WES) are two of the most popular next-generation sequencing (NGS) methodologi...

Background Genetic disposition is considered critical for identifying subjects at high risk for disease development. Investigating disease-causing and high and low expressed genes can support finding the root causes of uncertainties in patient care. However, independent and timely high-throughput next-generation sequencing data analysis is still a...

GVViZ is a user-friendly desktop-bioinformatics application, developed by Ahmed Lab to support RNA-seq driven gene expressions, regulation, and disease annotation analysis with dynamic heat map visualization. It is based on set of simple instructions, following those a user without strong bioinformatics background and programming skills can perform...

Despite significant scientific and medical discoveries, the genetics of novel infectious diseases like COVID-19 remains far from understanding. SARS-CoV-2 is a single-stranded RNA respiratory virus that causes COVID-19 by binding to the ACE2 receptor in the lung and other organs. Understanding its clinical presentation and metabolomic and genetic p...

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer, diabetes, cardiomyopathy, and COVID-19. With a progressive interpretation of the clinical, molecular, and genomic factors at play in diseases, more effective and personalized medical treatments are anticipat...

Supplementary Material: Integrative Clinical, Genomics and Metabolomics Data Analysis for Mainstream Precision Medicine to Investigate COVID-19

It’s been over 100 years since the word `gene’ is around and progressively evolving in several scientific directions. Time-to-time technological advancements have heavily revolutionized the field of genomics, especially when it’s about, e.g. triple code development, gene number proposition, genetic mapping, data banks, gene–disease maps, catalogs o...

We are entering the era of personalized medicine in which an individual's genetic makeup will eventually determine how a doctor can tailor his or her therapy. Therefore, it is becoming critical to understand the genetic basis of common diseases, for example, which genes predispose and rare genetic variants contribute to diseases, and so on. Our stu...

Manuscript Accepted!

Precision medicine is one of the recent and powerful developments in medical care, which has the potential to improve the traditional symptom-driven practice of medicine, allowing earlier interventions using advanced diagnostics and tailoring better and economically personalized treatments. Identifying the best pathway to personalized and populatio...

Healthcare data includes information about patients’ life style, medical history, claims data, metabolomics and genomics profiles. Adequate and analytic access to healthcare data has potential to revolutionize the field of medicine by detecting diseases at earlier stages and modelling complex biological interactions by integrating and analyzing kno...

Modern high throughput sequencing technologies are enormously contributing to the generation of heterogeneous genomic data of different sizes and kinds. In most of the cases, NGS data is first produced in the raw form, which is then demultiplexed into text based formats, representing nucleotide sequences i.e. FASTA and FASTQ formats for secondary a...

Daily alterations of routines and protocols create high, yet so far unmet demands for intelligent reaction monitoring, quality control and data management in molecular biology laboratories. To meet such needs, the “internet of things” is implemented here. We propose an approach which combines direct tracking of lab tubes, reactions and racks with a...

Background: The last decade has seen a dramatic increase in the availability of scientific data, where human-related biological databases have grown not only in count but also in volume, posing unprecedented challenges in data storage, processing, analysis, exchange, and curation. Next generation sequencing (NGS) advancements have facilitated and...

Objectives: Develop a multifunctional analytics platform for efficient management and analysis of healthcare data. Materials and Methods: Management, Analysis, and Visualization of Clinical Data (MAV-clic) is a Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant framework based on the Butterfly Model. MAV-clic extracts, cl...

PROMIS-Med: innovatively designed big data platform for receiving, managing, integrating, processing, analyzing and visualizing heterogeneous clinical, epidemiological, metabolomics, proteomics and genomics data for the promotion of practice transformation and implementation of precision medicine.

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalog...

SupplementaryMaterial: MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology, we are now accumulating ATAC-seq samples fr...

A step-by-step guide to I-ATAC, validating pipeline with two case studies

Daily alterations of routines and protocols create high, yet so far unmet demands for intelligent reaction monitoring, quality control and data management in molecular biology laboratories. To meet such needs, the internet of things is implemented here. We propose an approach which combines direct tracking of lab tubes, reactions and racks with a c...

One of the major challenges for the downstream analysis of amplicon data is to first demultiplex Fastq files based on the ligation of different oligonucleotides combinations. Match & Scratch Barcodes are a set of bioinformatics tools that support the analysis of PacBio sequenced long read amplicon data by detecting forward and reverse end adapter s...

Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology we are now accumulating ATAC-seq samples fro...

Supplementary Material: A standalone software platform for the interactive management and pre-processing of ATAC-seq

Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology we are now accumulating ATAC-seq samples fro...

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalog...

Mining biomedical images towards valuable information retrieval in biomedical and life sciences Zeeshan Ahmed, Saman Zeeshan and Thomas Dandekar doi:10.1093/database/baw118 In the above manuscript, the caption for Figure 2 should read as follows: Figure 2: Comparison of approaches towards heterogeneous and domain specific biomedical and scientifi...

The increasing amount of unparalleled heterogeneous genomic data generated today necessitates a robust platform for dealing with the practical issues of genomic data interoperability, structure, standardization, security, quality, pre-processing, governance development, long-term support, management of exponential growth of genomic applications and...

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results i...

MEDLINE citation count taken from the official website (http://www.nlm.nih.gov/bsd/medline_cit_counts_yr_pub.html) of the MEDLINE by the US national Library of Medicine (as of mid - November 2015)* Supplementary Material: Mining biomedical images towards valuable information retrieval in biomedical and life sciences Zeeshan Ahmed, Saman Zeeshan, T...

Supplementary Material: Mining biomedical images towards valuable information retrieval in biomedical and life sciences Zeeshan Ahmed, Saman Zeeshan, Thomas Dandekar

The increasing amount of heterogeneous Next Generation Sequencing (NGS) data generated today necessitates a robust platform for the efficient data storage, management, pre-processing, quality checking, analysis and visualization. Addressing each of these categories is a tremendous undertaking requiring high-level expertise from various disciplines....

Acknowledgements 1. Ahmed, Z., Dandekar, T. (2015) MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format [version 1; referees: 1 approved with reservations]. F1000Research., 4:1453. 2. Ahmed, Z., Saman, Z., Dandekar, T. (2014a) Developing sustainable software solutions for bioinformatics by the “Butterf...

Table of contents O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with Afri...

Human Genomics 2016, 10(Suppl 1):O1 Objectives From the first description by Leo Kanner [1], autism has been an enigmatic neurobehavioral phenomenon. The new genetic/genomic technologies of the past decade have not been as productive as originally anticipated in unveiling the mysteries of autism. The specific etiology of the majority of cases of au...

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalog...

Supplementary Material to MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

Product Data Management (PDM) produced desktop and web based systems to maintain the organizational technical and managerial data to increase the quality of products by improving the processes of development, business process flows, change management, product structure management, project tracking and resource planning. Though PDM is heavily benefi...

Product Data Management (PDM) produced desktop and web based systems to maintain the organizational technical and managerial data to increase the quality of products by improving the processes of development, business process flows, change management, product structure management, project tracking and resource planning. Though PDM is heavily benefi...

Software design and its engineering is essential for bioinformatics software impact. We propose a new approach ‘Butterfly’, for the betterment of modeling of scientific software solutions by targeting key developmental points: intuitive, graphical user interface design, stable methodical implementation and comprehensive output presentation. The foc...

A major challenge for mass spectrometric-based lipidomics, aiming at describing all lipid species in a biological sample, lies in the computational and bioinformatics processing of the large amount of data that arises after data acquisition. Lipid-Pro is a software tool that supports the identification of lipids by interpreting large datasets gener...

Acknowledgements Ahmed, Z., Michel, M., Saman, Z., Dandekar, T., Mueller, M J., Fekete A. (2015a). Lipid-Pro: A computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms. Bioinformatics 31, 1150-1153. Ahmed, Z., Dandekar, T., Mueller, M J., Fekete A. (2015b). Lipid-Pro:...

Acknowledgements Ahmed, Z., Michel, M., Saman, Z., Dandekar, T., Mueller, M J., Fekete A. (2015a). Lipid-Pro: A computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms. Bioinformatics 31, 1150-1153. Ahmed, Z., Dandekar, T., Mueller, M J., Fekete A. (2015b). Lipid-Pro:...

Field studies on arthropod ecology and behaviour require simple and robust monitoring tools, preferably with direct access to an integrated database. We have developed and here present a database tool allowing smart-phone based monitoring of arthropods. This smart phone application provides an easy solution to collect, manage and process the data i...

Supplementary Article: Lipid-Pro: A computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms

Unlabelled: A major challenge for mass spectrometric-based lipidomics, aiming at describing all lipid species in a biological sample, lies in the computational and bioinformatic processing of the large amount of data that arises after data acquisition. Lipid-Pro is a software tool that supports the identification of lipids by interpreting large da...

Field studies on arthropod ecology and behaviour require simple and robust monitoring tools, preferably with direct access to an integrated database. We have developed and here present a database tool allowing smart-phone based monitoring of arthropods. This smart phone application provides an easy solution to collect, manage and process the data i...

Supplementary to Ant-App-DB: A Smart Solution for Monitoring the Arthropods’ Activities, Experimental Data Management and Solar Calculations without GPS in Behavioural Field Studies

5th International Conference on Proteomics & Bioinformatics-2015